This is the first of two posts delineating the pedagogical approach of Herb Simon, credited with inventing the field of AI, for which he won a Turing award in 1975.

This is the first of two blog posts delineating the pedagogical approach of Herb Simon, the man credited with inventing the field of artificial intelligence, for which he won a Turing award in 1975. Simon was a polyglot social scientist, computer scientist and economics professor at Carnegie Mellon University. He later won the Nobel Prize in 1978 in economics for his work in organizational decision-making.

Herbert Simon, Pittsburg Post Gazette Archives

“Learning results from what the student does and thinks and only from what the student does and thinks. The teacher can advance learning only by influencing what the student does to learn.” –Herb Simon

Among his many accomplishments, Herb Simon was a pioneer in the field of adaptive production systems. He also identified the decision-making strategy “satisficing,” which describes the goal of finding a solution that is “good enough” and which meets an acceptability threshold, as opposed to “optimizing,” which aims to find an ideal solution.

Simon believed that human beings lack the cognitive resources to optimize, and are usually operating under imperfect information or inaccurate probabilities of outcomes. In both computer algorithm optimization and human decision-making, satisficing can save significant resources, as the cost of collecting the additional information needed to make the optimal decision can often exceed the total benefit of the current decision.

We live in a world where overwhelming amounts of information are at our very fingertips. Every month new educational software offerings are on the market. You can find tutorials to fix anything in your house, learn a new language for free, find lessons that teach you to dance, and watch video lectures from top universities in the topics of your choice.

I like to think of myself as a polyglot learner: I would love nothing better than to just take a year, or two, or ten, and learn as much as I can about everything. But unfortunately, I have limited time. How do I know which tutorials, lessons, and classes are worth the commitment of my time? How can I find a satisficing solution to the problem of becoming a more well-rounded learner and human being?

In Simon’s words, “information is not the scarce resource; what is scarce is the time for us humans to attend to it.” At Pedago we’ve been inspired by thinkers such as Simon to build a learning solution that makes the most of the scarce resource of your time, by employing curated streams of bite-sized lessons; rich, explorable connections between topics; interactive learn-by-doing experiences; and just the right amount of gamification. We want to enable you to craft your own learning experience, so that you can, as Simon would say, positively influence what you do and what you think.

Stay tuned for the second post in this series as we examine Simon’s modeling of human learning.

Given how useful the tinkering approach is for keeping learners motivated, how do we apply a similar approach to a subject like Finance?

By Artaxerxes (Own work) [CC-BY-SA-3.0], via Wikimedia CommonsMy friend Alfredo builds bikes as a hobby. He started by replacing a broken chain on his own bike. Then he upgraded his brakes. After a few more repairs, he understood the whole bike system well enough that he could gather all the parts and build one from scratch.

Experienced programmers generally learn new languages in a similar way. We get assigned to a new project for which there is an existing codebase that needs to be maintained or extended. Everything is mostly working, but something needs to be tweaked or added. So we tweak it. After working on five or ten features, we know the new language well enough that we could start a new project ourselves.

In more traditional educational environments, however, we tend to learn things the other way around. We start with simple, contrived building blocks and slowly work our way up to the point where we can comfortably manipulate a more complex and realistic system.

For example, a course that teaches the principle of the “Time Value of Money” is likely to start with a question like “if someone offered you $90 today or $100 a year from now, which one would you take?” This is, to say the least, an unrealistic scenario. But it is an introduction into the concept. After working through a number of similar examples in order to allow the student to master the math, the course will hopefully move on to a more reasonable explanation of how this concept is used in practice.

By Anna reg (Own work) [GFDL or CC-BY-SA-3.0-at], via Wikimedia CommonsNot that it was a bad course. I actually quite liked it. But this would be like if Alfredo had first worked on pedals, then wheels, then built himself a unicycle before moving on to gears and brakes. It would have been years before he had anything he could ride on. Knowing Alfredo, he would have had no hope of staying motivated for such a long time with no bike to show for it.

Given how useful the tinkering approach is for keeping learners motivated, how do we apply a similar approach to Finance? It turns out this is difficult to do because it often involves risking real money and waiting years to see any results. What a learner really needs is a safe environment to develop intuition around the long-term consequences of her decisions and to discover for herself the places where she needs to dig deeper.

At Pedago, developing alternative approaches to teaching tough topics is what we’re passionate about. Stay tuned over the coming months to see us tackle similar problems.

This post has been updated to include a clearer example. Thanks to Earthling for the feedback!

Bret Victor gave an entertaining talk on the history and/or future of computing at DBX 2013. In addition to the fascinating subject matter, Bret took the charming step of presenting with transparencies and an overhead projector.

Bret Victor gave an entertaining talk on the history and/or future of computing at DBX 2013. In addition to the fascinating subject matter, Bret took the charming step of presenting with transparencies and an overhead projector†.

We thought it’d be fun to recreate this effect. An evening of hacking resulted in a new toy: TransparenCSS (demo | source).

We’re abusing -webkit-mask-box-image, so for the full experience you’ll need Safari or Chrome. Firefox works, but you’ll be missing out on the “virtual glaucoma” effect.

Feel free to use TransparenCSS as a base for your own retro-future conference talks.

“After forty years of intensive research on school learning in the United States as well as abroad, my major conclusion is: What any person in the world can learn, almost all persons can learn, if provided with the appropriate prior and current conditions of learning.”

How do you convince a skeptic that climate change is real? The documentary Chasing Ice takes on this challenge to awe-inspiring effect.

How do you convince a skeptic that climate change is real? The documentary Chasing Ice takes on this challenge to awe-inspiring effect.

There’s no obvious connection between the melting of glaciers and online learning, so you might be wondering why this would be relevant to Pedago, an educational technology company. But bear with me.

The hero of the film, James Balog, turned to photography after finishing his master’s degree in Geology because he felt science was becoming too focused on numbers and statistics for him to enjoy. He believed he could make a greater impact through documenting Nature rather than dissecting it.

Thus, when faced with his own dawning realization that climate change was real, and human-influenced, he understood that facts, statistics, and lectures were ill-suited to sway the minds of a disbelieving public. He explored how best to use the tools of his trade–camera and ice axe–to make a difference.

His solution embodies the writer’s maxim to show and not tell. For three years, he and his team captured time-lapse images from Iceland, Alaska, Greenland, and Montana, then stitched them together. The resulting videos provide indisputable evidence that glaciers are receding ever more quickly. They are at once alarming, awesome, and visceral–attributes the standard “facts-and-graphs” discussions of climate change typically lack.

After watching this documentary, it really struck me that Balog was able to transform the conversation around a topic that is so frequently debated in the public space. Global warming is disputed more in American popular media than by scientists, its facts often treated as fictions promoted by activists. It’s difficult to convince people who are determined not to be convinced, even with the dramatic (but indirect) evidence of recent natural disasters. What can we learn from Balog’s feat?

I believe the key lesson is artful choice of data representation. The time-lapse images Balog’s team produced form physical evidence that is easily consumed. The viewer can wrap her mind around them, consider them as evidence, believe them or not with her own eyes. If the best way to understand the effects of global warming is to travel to a glacier and watch it calve icebergs or shrink into itself season after season, then bringing the key moments of this experience to a wider audience is certain to make a greater impact than presenting yet another statistic. A time lapse is worth a thousand graphs.

Balog’s accomplishment serves as a reminder to educators of the power in choosing novel representations for the material being presented. At the intersection of art, science, and technology, there is the potential for greater educational impact.

“I do not wish to reduce mathematics to literature or literature to mathematics. But I do want to argue that their respective ways of thinking are not as separate as is usually supposed.” ~Seymour Papert.